MailWizz MCP Server for LangChain 9 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect MailWizz through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"mailwizz": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using MailWizz, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About MailWizz MCP Server
Connect your MailWizz instance to any AI agent to automate your professional email marketing and audience management. This MCP server enables your agent to manage subscriber lists, control campaign lifecycles, and update subscriber data directly from natural language interfaces.
LangChain's ecosystem of 500+ components combines seamlessly with MailWizz through native MCP adapters. Connect 9 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
What you can do
- Campaign Oversight — List all email campaigns and retrieve detailed metadata and status information
- Mailing Control — Pause or unpause campaigns and manage their delivery lifecycle programmatically
- Audience Management — List all subscriber collections (lists) and retrieve their unique identifiers
- Subscriber Administration — Add, update, and remove subscribers from specific lists using their UIDs
- Data Ingestion — Sync subscriber information and manage custom fields across your email databases
- Self-Hosted Support — Works with any self-hosted MailWizz instance using your personal API keys
The MailWizz MCP Server exposes 9 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect MailWizz to LangChain via MCP
Follow these steps to integrate the MailWizz MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 9 tools from MailWizz via MCP
Why Use LangChain with the MailWizz MCP Server
LangChain provides unique advantages when paired with MailWizz through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine MailWizz MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across MailWizz queries for multi-turn workflows
MailWizz + LangChain Use Cases
Practical scenarios where LangChain combined with the MailWizz MCP Server delivers measurable value.
RAG with live data: combine MailWizz tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query MailWizz, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain MailWizz tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every MailWizz tool call, measure latency, and optimize your agent's performance
MailWizz MCP Tools for LangChain (9)
These 9 tools become available when you connect MailWizz to LangChain via MCP:
add_subscriber_to_list
Requires a list UID and subscriber data. Add a new subscriber to a list
delete_list_subscriber
Remove a subscriber from a list
get_campaign_details
Get details for a specific campaign
get_list_details
Get details for a specific subscriber list
list_email_campaigns
List all email marketing campaigns
list_list_subscribers
List subscribers in a specific list
list_subscriber_collections
List all subscriber lists
pause_email_campaign
Pause a running campaign
update_list_subscriber
Update an existing subscriber
Example Prompts for MailWizz in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with MailWizz immediately.
"List all active email campaigns in MailWizz."
"Add 'user@example.com' to my 'Main Leads' list (UID: 'lz987xyz')."
"Pause the email campaign with UID 'cp456def'."
Troubleshooting MailWizz MCP Server with LangChain
Common issues when connecting MailWizz to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersMailWizz + LangChain FAQ
Common questions about integrating MailWizz MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect MailWizz with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect MailWizz to LangChain
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.